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엠포스에서 빅데이터 분석을 해봤습니다~http://http://www.emforce.co.kr
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summary(cars)
## speed dist
## Min. : 4.0 Min. : 2.00
## 1st Qu.:12.0 1st Qu.: 26.00
## Median :15.0 Median : 36.00
## Mean :15.4 Mean : 42.98
## 3rd Qu.:19.0 3rd Qu.: 56.00
## Max. :25.0 Max. :120.00
## 'data.frame': 50 obs. of 2 variables:
## $ speed: num 4 4 7 7 8 9 10 10 10 11 ...
## $ dist : num 2 10 4 22 16 10 18 26 34 17 ...
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require(ggplot2)
require(plotly)
hhj_theme <- theme_classic(base_family="NanumGothic") +
theme(#axis.text.x = element_text(angle = 45),
strip.background = element_rect(colour = "white", fill = "white"),
axis.line = element_line(colour = "#EBEBEB"),
panel.spacing = unit(1, "lines")
)
theme_set(hhj_theme)
p <- ggplot(pressure, aes(temperature, pressure, color = "")) +
geom_point()
#call
htmltools::div(ggplotly(p), align="center")
p
엠포스의 빅데이터 분석을 통해 마케팅 분야의 …